{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test your pyiron installation\n",
    "The goal of this notebooks is to evaluate your pyiron installation - to identify which components are working and which are might need some additional configuration."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Your operation system\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'linux'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sys\n",
    "sys.platform  # ['linux', 'darwin', 'win32']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test pyiron \n",
    "Install pyiron from conda-forge: \n",
    "```\n",
    "conda install -c conda-forge pyiron\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# packages in environment at /srv/conda/envs/notebook:\r\n",
      "#\r\n",
      "# Name                    Version                   Build  Channel\r\n",
      "pyiron                    0.2.11             pyh9f0ad1d_0    conda-forge\r\n"
     ]
    }
   ],
   "source": [
    "! conda list pyiron"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install location\n",
    "List where conda is installed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/srv/conda/envs/notebook/lib/python3.7/site-packages/pyiron/__init__.py'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyiron\n",
    "pyiron.__file__  # location where pyiron is installed "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Your .pyiron configuration \n",
    "Check pyiron configuration, if pyiron is not configured, configure it using: \n",
    "```\n",
    "python\n",
    ">>> import pyiron\n",
    ">>> pyiron.install()\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'user': 'pyiron',\n",
       " 'resource_paths': ['/home/jovyan/resources'],\n",
       " 'project_paths': ['/home/jovyan/'],\n",
       " 'sql_connection_string': 'sqlite:////home/jovyan/resources/sqlite.db',\n",
       " 'sql_table_name': 'jobs_pyiron',\n",
       " 'sql_view_connection_string': None,\n",
       " 'sql_view_table_name': None,\n",
       " 'sql_view_user': None,\n",
       " 'sql_view_user_key': None,\n",
       " 'sql_file': '/home/jovyan/resources/sqlite.db',\n",
       " 'sql_host': None,\n",
       " 'sql_type': 'SQLite',\n",
       " 'sql_user_key': None,\n",
       " 'sql_database': None,\n",
       " 'project_check_enabled': True,\n",
       " 'disable_database': False}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyiron_base import Settings\n",
    "s = Settings()\n",
    "s._configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Your pyiron working directory \n",
    "pyiron restricts the users to execute notebooks only in the `project_paths`. We check if the current working directory is part of the `project_paths`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyiron import Project\n",
    "pr = Project('.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NGLview for visualizing atomistic structures\n",
    "NGLView is used for visualisation of atomistic structures. First we check if NGLview was installed using conda: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# packages in environment at /srv/conda/envs/notebook:\r\n",
      "#\r\n",
      "# Name                    Version                   Build  Channel\r\n",
      "nglview                   2.7.5              pyh5ca1d4c_0    conda-forge\r\n"
     ]
    }
   ],
   "source": [
    "! conda list nglview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For jupyter notebooks nglview can be installed using: \n",
    "\n",
    "```\n",
    "conda install -c conda-forge nglview\n",
    "jupyter nbextension install nglview --py --sys-prefix\n",
    "jupyter nbextension enable nglview --py --sys-prefix\n",
    "```\n",
    "\n",
    "For jupyterlab the installation is slightly different: \n",
    "```\n",
    "conda install -c conda-forge nodejs nglview\n",
    "jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build\n",
    "jupyter labextension install nglview-js-widgets\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8e74af25dd9246d4bc680137bea3b686",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "_ColormakerRegistry()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8f7ac643d19c4a96807b70df0f7f75cf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import nglview\n",
    "nglview.demo()  # You should see a molecule which you can rotate in 3D "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulation codes\n",
    "pyiron does not include any simulation codes, these have to be installed separatley:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lammps \n",
    "We start with installing Lammps directly from Anaconda (the conda-forge channel provides the executables for Linux and Mac Os X): \n",
    "```\n",
    "conda install -c conda-forge lammps \n",
    "```\n",
    "For windows Lammps is available from the pyiron conda channel: \n",
    "```\n",
    "conda install -c pyiron lammps \n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# packages in environment at /srv/conda/envs/notebook:\r\n",
      "#\r\n",
      "# Name                    Version                   Build  Channel\r\n",
      "lammps                    2020.03.03         py37_mpich_2    conda-forge\r\n"
     ]
    }
   ],
   "source": [
    "! conda list lammps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job static was saved and received the ID: 1\n"
     ]
    }
   ],
   "source": [
    "from pyiron import Project\n",
    "pr = Project('lammps')\n",
    "lmp = pr.create_job(pr.job_type.Lammps, 'static')\n",
    "lmp.structure = pr.create_structure('Fe', 'bcc', 2.55)\n",
    "lmp.potential = 'Fe_C_Hepburn_Ackland_eam'\n",
    "lmp.run()  # The job static was saved and received the ID: 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lammps interactive \n",
    "The conda-forge channel includes the Lammps executables as well as the Lammps library, unfortunatley this is not available for windows. Therefore for Windows we recommend installing pyiron using the Linux subsystem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job interactive was saved and received the ID: 1\n",
      "[-6.38884508 -6.38884508 -6.38884508]\n",
      "[-6.38884508 -6.38884508 -6.38884508 -6.38884508]\n"
     ]
    }
   ],
   "source": [
    "from pyiron import Project\n",
    "pr = Project('lammps')\n",
    "lmp = pr.create_job(pr.job_type.Lammps, 'interactive')\n",
    "lmp.structure = pr.create_structure('Fe', 'bcc', 2.55)\n",
    "lmp.potential = 'Fe_C_Hepburn_Ackland_eam'\n",
    "lmp.server.run_mode.interactive = True\n",
    "lmp.run()  # The job interactive was saved and received the ID: 1\n",
    "print(lmp.output.energy_tot)  # [-6.38884508]\n",
    "lmp.run()\n",
    "print(lmp.output.energy_tot) # [-6.38884508 -6.38884508]\n",
    "lmp.interactive_close()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sphinx \n",
    "The Sphinx DFT code is developed at the MPIE and it can be installed for Linux using the conda-forge channel: \n",
    "```\n",
    "conda install -c conda-forge sphinxdft\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# packages in environment at /srv/conda/envs/notebook:\r\n",
      "#\r\n",
      "# Name                    Version                   Build  Channel\r\n",
      "sphinxdft                 2.6.1                h6ced99e_5    conda-forge\r\n"
     ]
    }
   ],
   "source": [
    "! conda list sphinxdft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job static was saved and received the ID: 2\n",
      "The files are already compressed!\n"
     ]
    }
   ],
   "source": [
    "from pyiron import Project\n",
    "pr = Project('sphinx')\n",
    "lmp = pr.create_job(pr.job_type.Sphinx, 'static')\n",
    "lmp.structure = pr.create_structure('Fe', 'bcc', 2.55)\n",
    "lmp.run()  # The job static was saved and received the ID: 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GPAW \n",
    "Besides Sphinx is GPAW a second opensource DFT code available for pyiron. For both Mac Os X and Linux GPAW is available from conda-forge available: \n",
    "```\n",
    "conda install -c conda-forge \n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# packages in environment at /srv/conda/envs/notebook:\r\n",
      "#\r\n",
      "# Name                    Version                   Build  Channel\r\n",
      "gpaw                      19.8.1             py37_nompi_0    conda-forge\r\n"
     ]
    }
   ],
   "source": [
    "! conda list gpaw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job static was saved and received the ID: 3\n"
     ]
    }
   ],
   "source": [
    "from pyiron import Project\n",
    "pr = Project('gpaw')\n",
    "lmp = pr.create_job(pr.job_type.Gpaw, 'static')\n",
    "lmp.structure = pr.create_structure('Fe', 'bcc', 2.55)\n",
    "lmp.run()  # The job static was saved and received the ID: 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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